Hey Nadav,
Hmm. Just noticed there are two least squares algorithms. The one in
scipy/optimize/minpack.py (which you are using) can output quite a bit of data,
but it isn't obvious that one of them is the residuals to me. Maybe Travis O.
has more idea about this.
There is also a scipy.linalg.lstsq (note spelling difference). This one uses
singular value decomposition while the other one uses minpack routines. It's
doc string doesn't say much about it, but looking at the code, its return value
is:
def lstsq(A, B, rcond=None):
...
return x, resids, rank_v, s
I'm betting the second one is what you want.
Now the next question is why the heck there are two least squares algorithms in
SciPy. For that, I have no good answer, other than its still evolving... :-)
see ya,
eric
----- Original Message -----
From: "Nadav Horesh" <nadavh at envision.co.il>
To: <scipy-user at scipy.net>
Sent: Wednesday, February 20, 2002 3:45 AM
Subject: [SciPy-user] Eror estimation in leastsq
> Hello,
>> Is there a way to estimate the errors (standard deviations) of each
> optimized parameter, from the
> output of scipy.opimize.leastsq?
>> Nadav.
>> _______________________________________________
> SciPy-user mailing list
>SciPy-user at scipy.net>http://www.scipy.net/mailman/listinfo/scipy-user>